The December 2022 issue of IEEE Spectrum is here!

Close bar

The Real Story of Stuxnet

How Kaspersky Lab tracked down the malware that stymied Iran’s nuclear-fuel enrichment program

10 min read
Illustration: Brian Stauffer
Illustration: Brian Stauffer
Red

Computer cables snake across the floor. Cryptic flowcharts are scrawled across various whiteboards adorning the walls. A life-size Batman doll stands in the hall. This office might seem no different than any other geeky workplace, but in fact it's the front line of a war—a cyberwar, where most battles play out not in remote jungles or deserts but in suburban office parks like this one. As a senior researcher for Kaspersky Lab, a leading computer security firm based in Moscow, Roel Schouwenberg spends his days (and many nights) here at the lab's U.S. headquarters in Woburn, Mass., battling the most insidious digital weapons ever, capable of crippling water supplies, power plants, banks, and the very infrastructure that once seemed invulnerable to attack.

Recognition of such threats exploded in June 2010 with the discovery of Stuxnet, a 500-kilobyte computer worm that infected the software of at least 14 industrial sites in Iran, including a uranium-enrichment plant. Although a computer virus relies on an unwitting victim to install it, a worm spreads on its own, often over a computer network.

Keep reading...Show less

This article is for IEEE members only. Join IEEE to access our full archive.

Join the world’s largest professional organization devoted to engineering and applied sciences and get access to all of Spectrum’s articles, podcasts, and special reports. Learn more →

If you're already an IEEE member, please sign in to continue reading.

Membership includes:

  • Get unlimited access to IEEE Spectrum content
  • Follow your favorite topics to create a personalized feed of IEEE Spectrum content
  • Save Spectrum articles to read later
  • Network with other technology professionals
  • Establish a professional profile
  • Create a group to share and collaborate on projects
  • Discover IEEE events and activities
  • Join and participate in discussions
Colorful chip with wires coming out of it surrounded by large metal plates.

Engineers probe the performance of noisy bits that, when working together, may solve some problems better than quantum computers.

Lang Zeng/Beihang University

A large universal quantum computer is still an engineering dream, but machines designed to leverage quantum effects to solve specific classes of problems—such as D-wave’s computers—are alive and well. But an unlikely rival could challenge these specialized machines: computers built from purposely noisy parts.

This week at the IEEE International Electron Device Meeting (IEDM 2022), engineers unveiled several advances that bring a large-scale probabilistic computer closer to reality than ever before.

Keep Reading ↓Show less

AI for Wireless

The key to overcoming complexity in modern wireless systems design

4 min read
Diagram showing machine learning workflows
MathWorks

This is a sponsored article brought to you by MathWorks.

The evolution of mobile wireless technology, from 3G/4G to 5G, and introduction of Industry 4.0, have resulted in the ever-increasing complexity of wireless systems design. Wireless networks have also become more difficult to manage due to requirements necessitating optimal sharing of valuable resources to expanding sets of users. These challenges force engineers to think beyond traditional rules-based approaches with many are turning to artificial intelligence (AI) as the go-to solution to face the challenges introduced by modern systems.

From managing communications between autonomous vehicles, to optimization of resource allocations in mobile calls, AI has brought the sophistication necessary for modern wireless applications. As the number and scope of devices connected to networks expands, so too will the role of AI in wireless. Engineers must be prepared to introduce it into increasingly complex systems. Knowing the benefits and current applications of AI in wireless systems, as well as the best practices necessary for optimal implementation, will be key for the future success of the technology.

Keep Reading ↓Show less
{"imageShortcodeIds":[]}